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Kazunori Hashirii

dblp:81/7736 · DBLP profile ↗
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2ranked-venue papers
0as first author
0since 2021 · last 2014
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 1Systems, architecture and hardware · 1Applied, interdisciplinary, general and emerging computing · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Artificial intelligence
2 papers
Robot manipulation · 100%

Topics — the 4 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Robotics › Robot manipulation
grasping
0.212014
Analysis, Classification, and Design of Tendon-Driven Mechanisms · IEEE Trans. Robotics 2014
Robotics › Robot manipulation › robot actuation
tendon-driven mechanism
0.212014
Analysis, Classification, and Design of Tendon-Driven Mechanisms · IEEE Trans. Robotics 2014
Robotics › Robot manipulation › robot design › mechanism design
underactuated mechanism
0.212014
Analysis, Classification, and Design of Tendon-Driven Mechanisms · IEEE Trans. Robotics 2014
Robotics › Robot manipulation
robotic hand design
0.012009
Design and control of underactuated tendon-driven mechanisms · ICRA 2009

Methods — techniques the papers use, named apart from their topics

controllability analysis · 0.2bias force analysis · 0.2tendon-driven transmission · 0.1mechanism classification · 0.1
YearPublicationVenuePosition
2014 Analysis, Classification, and Design of Tendon-Driven Mechanisms
abstract
This paper analyzes tendon-driven mechanisms (TDMs) with active and passive tendons and proposes a method for designing TDMs. First, we group TDMs into six classes according to their controllability and the number of driving degrees of freedom. In this classification system, the conventional underactuated mechanisms are grouped into three classes, two of which have often previously been grouped together although they have different manipulation abilities. Next, we analyze bias forces to separate and decouple a given TDM into several smaller TDMs. Finally, we propose a design method for combining smaller TDMs into an appropriate TDM. Using this method, we can easily determine an appropriate tendon transmission that meets the requirements for the number of tendons, the hardware of the tendon routing, and arbitrary joint constraint that has useful applications in prosthetic and biomimetic hands. Numerical examples show that the proposed method guarantees a nonsingular series actuation transmission and that the designed underactuated TDMs could achieve arbitrary stiffness independent of the actuation effort compared with the conventional underactuated TDM with torsion springs.
Ryuta Ozawa, Hiroaki Kobayashi, Kazunori Hashirii
IEEE Trans. Robotics3
2009 Design and control of underactuated tendon-driven mechanisms
abstract
Many robotic hands or prosthetic hands have been developed in the last several decades, and many use tendon-driven mechanisms for their transmissions. Robotic hands are now built with underactuated mechanisms, which have fewer actuators than degrees of freedom, to reduce mechanical complexity or to realize a biomimetic motion such as flexion of an index finger. The design is heuristic and it is useful to develop design methods for the underactuated mechanisms. This paper classifies mechanisms driven by tendons into three classes, and proposes a design method for them. The two classes are related to underactuated tendon-driven mechanisms, and these have been used without distinction so far. An index finger robot, which has four active tendons and two passive tendons, is developed and controlled with the proposed method.
Ryuta Ozawa, Kazunori Hashirii, Hiroaki Kobayashi
ICRA2